The final architecture, SENet [1]}, introduces the squeeze-and-excitation block that adaptively re-calibrates the channel-wise feature responses by modelling the interdependencies between channels to automatically acquire the importance of each feature channel. SENet is the winner of ILSVRC 2017 classification challenge.
